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Indian Institute of Management, Ahmedabad - IIMA

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IIMA, 2018

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Text by Jannik C. ©
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HOUSING.COM

A Case Study


Table of Contents

Background 4

Housing – A Multisided Platform (MSP) 5

What Housing Did Right? 5

Service Package To Home Buyers – Demand Side 5

Service Package To Real Estate Agents/Brokers – Supply Side 7

Housing’s Service Characteristics 9

How Housing Tracks Service Quality? 10

Operations 11

What Went wrong in terms of Service? 12

Recommendations 14


Background

Housing (formerly called Housing.com) was started by a group of 12 IITians in 2012 with the vision to transform the online real estate sector in India. It professed to bring greater transparency and ultimately become the most trusted real estate platform in the country. It’s approach, at the most basic level, was rooted in technology and authentic data.

Backed by marquee investors like Softbank, Helion and Nexus Venture Partners, Housing was valued at about $250 million by late 2014 after having raised north of $120 million since its inception.

However, things started to go sour as the real estate market slumped even as the company spent exuberant amounts in salaries and in general operations. There was also disagreement over the focus of the company at the top management level. With increased investor’s impetus on profitability and pressure on reducing the massive operational burn rate, the company took to cutting costs and down-sized its workforce in three rounds, which brought the total employee count from 2,500 at its peak in June 2015 to about 1,000 in June 2017. All of these factors affected the key service metrics and the company lost its footing in this competitive and fragmented market of real estate.

The valuation of company eroded to $70-$75 million and was ultimately acquired by News Corp backed real estate portal PropTiger.

This report attempts to analyze what Housing did right in terms of its service and operations which captured the imagination of 3.5 million monthly visitors on its website. It was the first real estate portal which strongly believed in the authenticity of information - be it real photos of houses, the 360 panorama view of land plots, verified neighborhood details or the accurate mapped location of each listing.

It gave users a powerful tool that allowed them to conduct a thorough home scout without actually necessitating their physical presence. We would look at what went behind in creating this seamless experience, complete with brilliant visualization and an intuitive and user friendly interface.

The report also attempts to understand the key factors that led to its downfall from its once elevated status, such as askew engagement with its suppliers (brokers, builders, owners etc.), negligent post sales service, fall in quality of listings and lack of differentiation vis-à-vis competitors. Though Housing rode up on the credence of great design backed by data, it failed to gain the single-most thing that it stood for: the trust of its suppliers & users, more salient in a high value & low frequency transaction like home buying or selling.

This report required investigative research for which we engaged with the workers and management of Housing to understand their service benchmarks, operations and outcomes. Moreover, we reached out to users, who had used Housing or similar portals in their search for rental or resale properties, to understand the value they perceive. We also talked to few brokers/real estate agents of Mumbai region to discuss the service parameters of Housing and its competitors, and how have they chang.....[read full text]

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This makes sure the process is hassle free and has a high rate of conversion.

  1. Reliability of data

The data is up-to-date since Housing runs a decay algorithm in backend which automatically deactivates rental properties after 3 months and resale properties in 6 months, thereby ensuring that the flats that users can see are actually those inventory which are available in the market and aren’t yet sold out.


  1. Explicit Services

  1. Availability (On web, mobile, and toll-free number)

India’s first map based property portal. This feature provides users with complete data on their prospective homes down to the last by-lane - from real photos to exact locations to neighbourhood details. Moreover, Housing mobile app for users showcases the same attributes. The users can view the properties along with all the relevant details without physically visiting the property by using their web browser or mobile app.

The all three (0333333333) toll free number also gave the users another medium to get information and expedite their home search process (This was discontinued in 2016)

  1. Comprehensiveness of Information

Housing’s Data Science Lab (DSL) intends to periodically enhance its product quality and functioning through constant market analysis and research. The team has come up with some algorithms like the Housing Lifestyle Rating, Child Friendliness Index, and Price Heat Maps etc. which provides users with more comprehensive view of not just the flat in isolation, but the entire locality and city put together.

Area-based pricing models, price analytics for new projects etc. are few other differentiators that allows buyers to make more informed choice.

  1. Credibility and Reliability

Sourcing each property physically from certified brokers keeps the quality of inventory in check and gives credibility to the information that is put up, especially factors like price, area etc. This is a huge differentiating factor in an industry which is plagued by the lack of credible and reliable data. More than 50% of the listings in competitor portals like Magic Bricks and 99Acres are either fake, put up by brokers themselves to gain more visibility as they have self upload facility which doesn’t need any physical verification, or are inaccurate, put up by the same brokers to get leads directed to them.


  1. .....

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  1. Account Manager

The broker is assigned a dedicated Housing employee who serves both as a data collector as well as business development/sales executive. The broker can request an appointment depending on whether he wants to list a property or buy a ad-product to increase his visibility on the website. This service of on-demand property collection as well as sales visits is completely free.

  1. Access to Buyers - Leads Generation and Management

Brokers’ properties get displayed to large number of users on the platform, which gets converted to leads. The broker is given the capability of saving & managing those leads, either through the broker app or through the web-based lead management portal. Moreover, if the same lead calls again, the system would be able to identify the lead and give a snapshot of the same (just like true caller) such that the broker gets a heads-up before taking the call.


  1. Implicit Services

  1. Exclusivity

Paid brokers are given a feeling of exclusivity by giving them locality-level demand trends, preferential visibility, higher number of organic leads, and flexibility to update prices.

  1. Privacy

If a broker uploads a property, Housing ensures that it doesn’t display the exact address on the flat on the portal. Though a user can get to see the locality and the neighbouring areas on the map, he won’t know the street level data. This ensures that other brokers can’t poach the same flat from the owner. Hence, the data given by the broker remains secure even as its open for everyone to see.

  1. .....

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  1. Customer Experience Realm

In the case of both buyers as well as sellers, there is active participation. The buyers/users actively browse through the catalogue of property photos as well as consume the relevant content about the locality, be it price trends, expert consultation etc. Similarly, the sellers be it owners or brokers, need to either schedule a visit from the data collection team and give the details/photos for the property to go live, or use the Housing Agent App to either edit the property details or avail the leads he has received on the same property.

Moreover, the experience received at both the sides is more of absorption of information rather than being immersed in an activity.


Passive Participation

Active Participation

Absorption

Entertainment

Education

Immersion

Esthetic

Escapist

How Housing Tracks Service Quality?

  1. Demand Side

Housing employs user engagement metrics such as bounce rate (% of visitors who quit after landing the first page), average daily time spent on site, click to lead conversion ratio etc. as the indicators of service quality on the demand side. In 2014, Housing was doing better than its competitors in all the key engagement metrics as depicted below:


©Housing Business Module 2014 – Sourced from Nitin T.S, Head of Operations, Housing.com


  1. Supply Side

On the supply side, broker engagement is measured through operational metrics such as percentage of monthly active brokers (unique brokers who listed property in that given month), time spent on Housing for Agents App, the number of properties listed vis-à-vis competitors in a locality, paid packages bought etc. Moreover, internal quality check of data collection team is done through performance metrics like number of tickets (quality escalations due to errors), efficiency (average # of flats collected per day), broker touch rate (unique brokers who gave flats) etc.

Moreover, the quality of data collected in terms of the photo clarity, information integrity etc. is inspected by a 50 membered quality team which doesn’t allow a property to go live until the data collector recollects the same property according to the set guidelines. Also an audit team is set in place which ensures that no data collector or broker is able to circumvent the system and post a f.....

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    1. Specification Gap (Gap 2)

It is specified that brokers can list only rental or resale properties which are either furnished, semi-furnished or unfurnished. Moreover, under-construction properties couldn’t be taken as they don’t meet the quality of platform that Housing professes to uphold even if it meant giving up a sizeable chunk of the market. However, there is no clear line drawn between an unfurnished flat and an under-construction flat, which leads to ambiguity resulting in data-collectors, who are incentivised on the number of flats collected, to upload the under-construction properties which later gets rejected by the quality team.

This rejection of properties alienates the brokers who had to spend considerable time and effort sourcing the flats. Moreover, if any of such flats escapes the quality check (such instances increased exponentially once volume increased), the user who comes to the site sees a below-par inventory and the search experience takes a hit.

    1. Delivery Gap (Gap 3)

The lead delivery to brokers had two major faults. First, the mobile ‘Housing Broker App’ which was launched for the sole of purpose of tracking leads (their details, requirements, last contacted etc.) and managing properties met with lot of technical snags in the first one year of launch, resulting in cases like leads getting lost etc. Secondly, there is no system to control the flow of leads such that a good property (in terms of possession date, newness of building etc.) in a high demand locality (in terms of affordability, accessibility etc.) causes a flood of requests to one broker which is beyond his capacity to service.

Many a times, such high demand property would be long gone before the property is decayed from the system and the leads stop flowing in. This creates chagrin at both sides, brokers getting irritated by non-stop calls for a property that doesn’t exist and users getting dissatisfied by non-responsiveness by such brokers. On the other hand, there are brokers sitting disgruntled who don’t have enough leads and could have given better service to the user by leveraging his broker network.

    1. .....

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The latter was obviously tougher. Hence, this led to a cycle where although the collection was high, it was effectively useless for the people who are coming to search. Hence, this created a loop in which poor supply draws in lesser demand, and lesser demand makes it harder for operations to source better supply.


  1. Management Myopia

The management, under pressure of profitability from the board, took a short-sighted approach to simultaneously push for more data collection as well as monetisation. Even as more collection under tight budget led to the fall of inventory quality (which later translated into reduced demand), the push for monetisation led to exclusion of non-paying small brokers who were the primary sources of supply initially.

Hence, with both supply and demand shrinking, the paid brokers were left with low performing ad-products, which led to fewer repeat purchases. As different efforts to monetise the shrinking broker base failed, Housing could only see itself merge with another to stay afloat.

Recommendations

Focus on Unit Economics

Multisided Platform can’t be sustainable if with each addition of supply, the overall cost per unit doesn’t go down. The unit cost can go down only by leveraging technology or innovating operations such that the quality isn’t compromised even as company scales up. Housing can leverage its existing broker app platform to give the brokers more autonomy in uploading flats (self-upload feature) while keeping a strict quality check at backend, such that it can reduce its operational load, cut its costs and move towards a model which is more customer friendly and easy to monetise, developed on the back of equitable distribution of demand through accurate forecasting.

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